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. 2015 Apr:2015:200-204.
doi: 10.1109/ISBI.2015.7163849.

COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM

Joakim Andén  1 , Eugene Katsevich  2 , Amit Singer  1
Affiliations

COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM

Joakim Andén et al. Proc IEEE Int Symp Biomed Imaging. 2015 Apr.

Abstract

Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.

Keywords: 3D reconstruction; Cryo-EM; classification; conjugate gradient; covariance; heterogeneity; single particle reconstruction; structural variability.

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Figures

Fig. 1
Fig. 1
Sample projection images from the synthetic dataset (a,b) and experimental images of the 70S ribosome (c,d).
Fig. 2
Fig. 2
(a) The eigenvalue histogram of Σn obtained from synthesized data. (b) The histogram of the coordinate α1.
Fig. 3
Fig. 3
(a) The eigenvalue histogram for Σn obtained from experimental images of the 70S ribosome complex. (b) The histogram of the coordinate α1. (c,d) Cross-sections of estimated volumes.
See this image and copyright information in PMC

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